The present disclosure relates to an apparatus and method for image processing. In particular, the disclosure relates to an apparatus and method for image processing by which a feature analysis of an image is allowed to be more readily carried out.
An application range of a pathology diagnosis by a Digital Pathology Imaging (DPI) system has spread to a cell diagnosis as well in addition to a past tissue diagnosis.
The tissue diagnosis is a method in which in an inspection, an operation or the like, a site of involvement, for example, is cut out by using a surgical knife to be harvested, and the site of involvement is then thinly sliced and stained to be observed by using a microscope. In the tissue diagnosis, in general, cells are observed as a set, and it, for example, is diagnosed whether or not the cell group has an abnormality in a size, a shape, an arrangement pattern, and the like of the cells, or whether or not a cell which is essentially absent exists in the cell group.
On the other hand, the cell diagnosis is a method in which a cell (sputum cytodiagnosis) which has fallen off by itself, a cell (exfoliative cytodiagnosis) which has been peeled off, a cell (aspiration cytology) which has been aspirated through needle prick or the like is stained and is then observed by using a microscope. In the cell diagnosis, in general, a less number of cells are observed, thereby diagnosing whether or not there is an abnormality in each of the cells, a size, a shape, etc. of a nucleus of each of the cell.
In the DPI system, images of the tissues and the cells (observation images obtained through the microscope) are managed in the form of digital data. For this reason, various pieces of image processing can be suitably subjected to the observation images (i.e., digital data) in accordance with a use application or the like.
A feature analysis about an image like detection of a Region Of Interest (ROI) is known as one of the various pieces of image processing. In this case, by analyzing the features of the image, the analysis result can be utilized in other various pieces of image processing and other various diagnosises.
For example, a method was devised in which in the tissue diagnosis, the ROI detection based on edge detection was carried out for the observation image, and confluency of the cells was calculated from the detection result, thereby specifying a carcinoma cell. This method, for example, is disclosed in Japanese Patent Laid-Open No. 2009-175040.
On the other hand, in the case of the cell diagnosis, in general, a large number of regions (blank regions), unnecessary for the observation, in which no cell is present exist in an image of the cells observed as compared with the case of the tissue diagnosis in many cases.
In addition, in the case of the cell diagnosis, the observation object is not a cut surface of the tissue unlike the tissue diagnosis. Therefore, for example, the cells overlap one another and the cells are different in size from one another in some cases. In a word, a focal point position in a depth direction differs every portion within the observation area in some cases. In order to cope with such a situation, in the case of the cell diagnosis, focal point position control in the depth direction which is referred to as so-called Z stack and plural observation images which are different from one another in the focal point position in the depth direction are generated in some cases.
As has been described, the observation image in the cell diagnosis has the features different from those in the tissue diagnosis in many cases. Therefore, the feature analysis which is suitable for the features of the observation image for the cell diagnosis is preferably carried out for the observation image for the cell diagnosis.